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Digital Twins: Forecasting, Optimizing, Decarbonizing and Ensuring Safety

Digital Twins: Forecasting, Optimizing, Decarbonizing and Ensuring Safety

My two grandchildren are twins. I can tell you a few things about them. They are definitely not identical. They see the world in different ways. They are pretty insightful. And their insights are different and complementary.

 

So what would I see if I looked at them digitally? Well, if I looked at a genetic map, they would probably be pretty close to identical. But if I started to look at a medical profile, one has allergies and one doesn’t, one is bigger than the other. And a mental profile?  Well, here’s where they diverge in their personalities and thought processes.

 

What is the correct “digital twin,” or digital view, to use? I think we would all agree it needs to be a combination of these views, and others, to profile each person, to get insight into their wellness and to predict their future.

 

So what is a digital twin for a process industry asset? What is AspenTech’s definition of digital twins? And where do we believe digital twins are going in the future?

 

 

A Digital Twin Is Really Multiple Views of the Asset, Business Processes and People

 

Just like my oversimplified example of my twin grandchildren makes clear, the digital twin of a process, asset and operation must be a combination of multiple digital views and models. These can be looked at separately or together to gain insight, to optimize, to improve, to predict performance of the asset and to give a true picture of how a “connected worker” can achieve the best possible performance. 

 

Process industry assets are complex. There are many ways to look at them — and, in fact, many ways you must look at them — to first and foremost ensure they are safe, but then to ensure they are performing the desired outcome (a basket of products) in the most sustainable, high-quality, predictable, repeatable and profitable manner possible.

 

A few months ago I had an interesting conversation over lunch with LNS Research’s Joe Perino.  He was digging deeply into how different organizations were defining digital twin. He concluded, exactly as we have at AspenTech, that there is no one digital twin of an asset or operation. There is a spectrum of them.

 

In fact, Joe had performed an analysis of one mid-size refinery in the U.S. Midwest, and he had concluded that it would take several thousand individual “digital twin models” to fully describe everything of importance about that refinery. (Clearly, that number of digital twins would not be built. The point is there may be a different answer, depending on that asset’s business, sustainability and margin challenges).

 

As shown in this graphic, digital twins are an evolving digital profile of the historical, current and future behavior of a physical object or process that helps optimize business performance.

 

They are based on models and real-time data across multiple different dimensions, creating an evolving profile of the object or process in the digital world. This can provide important insights on system performance, leading to actions in the physical world, such as a changes in process design and operation, as well as safety and maintenance improvements.